The current research aims to determine the requirements of Trends of International Mathematics and Science Study (TIMSS 2019) and to find out the extent to which the content of science textbooks for grades (1-4) in the Sultanate of Oman includes the requirements of (TIMSS 2019). Only the Cognitive Process dimension has been considered when conducting the analysis. The study population includes all science books from the first to the fourth grade for the academic year 2021-2022. The study identified and organized the requirements in the study tool, which is a list of requirements of (TIMSS 2019). After confirming its validity and reliability, the analysis was performed, and data were collected and analyzed statistically using frequencies and percentages. The results showed that all domains (knowledge, Applying, and Reasoning) and all cognitive skills for each domain were included in each grade, but the percentages included in the books differed always from those specified in the requirements of (TIMSS 2019). The rank of the included domains in grades 1, 3, and 4, were as follows: first, knowledge, second, Applying, and finally, Reasoning, which is the same rank proposed by (TIMSS 2019). However, the rank for grade 2 was different where Applying came first while Reasoning and knowledge came in the second and third ranks respectively. When frequencies and ratios were calculated for each of the three domains of cognitive processes cumulatively over the four years (1-4), an interesting result popped out. The percentage included for each of the three domains is close to the percentages specified by (TIMSS 2019). This means that the science textbooks (Cambridge) designed for students from the first grade to the fourth grade have balanced well between the percentages included and the percentages specified by (TIMSS 2019), but over the four years and not over one year only, as the difference between the percentages included and the percentages specified by (TIMSS 2019) in the field of knowledge was about 6.5 percentage points in favor of the percentage included, and the difference in the field of Applying was about 4.5 points Percentage in favor of the specified percentage. As for Reasoning, the difference was less than two points only in favor of the specified percentage, which means that there is a relatively greater focus on knowledge and relatively less on Applying and Reasoning.
<span>One of the main difficulties facing the certified documents documentary archiving system is checking the stamps system, but, that stamps may be contains complex background and surrounded by unwanted data. Therefore, the main objective of this paper is to isolate background and to remove noise that may be surrounded stamp. Our proposed method comprises of four phases, firstly, we apply k-means algorithm for clustering stamp image into a number of clusters and merged them using ISODATA algorithm. Secondly, we compute mean and standard deviation for each remaining cluster to isolate background cluster from stamp cluster. Thirdly, a region growing algorithm is applied to segment the image and then choosing the connected regi
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New data on jumping spiders (Salticidae) and tangle-web spiders (Theridiidae) of Armenia are provided on the basis of recently collected specimens in various regions of Armenia. One species, Ballus rufipes (Simon, 1868) is recorded as new to the Caucasus Region, in addition to the following species: Neon reticulatus (Blackwall, 1853), Pellenes brevis (Simon, 1868), Salticus scenicus (Clerck, 1757) and Synageles dalmaticus (Keyserling, 1863) that belong to a family Salticidae, are recorded in Armenia for the first time.
A further 7 species of Theridiidae are recorded in Armenia for the first time Kochiura aulica (C. L. Koch, 1838), Steatoda albomaculata (De Geer, 1778), Steatoda bipunctata (Linnaeus, 1758), Steatoda castanea Clerk, 175
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The dependable and efficient identification of Qin seal script characters is pivotal in the discovery, preservation, and inheritance of the distinctive cultural values embodied by these artifacts. This paper uses image histograms of oriented gradients (HOG) features and an SVM model to discuss a character recognition model for identifying partial and blurred Qin seal script characters. The model achieves accurate recognition on a small, imbalanced dataset. Firstly, a dataset of Qin seal script image samples is established, and Gaussian filtering is employed to remove image noise. Subsequently, the gamma transformation algorithm adjusts the image brightness and enhances the contrast between font structures and image backgrounds. After a s
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Explainable Artificial Intelligence (XAI) techniques enable transparency and trust in automated visual inspection systems by making black-box machine learning models understandable. While XAI has been widely applied, prior reviews have not addressed the specific demands of industrial and medical inspection tasks. This paper reviews studies applying XAI techniques to visual inspection across industrial and medical domains. A systematic search was conducted in IEEE Xplore, Scopus, PubMed, arXiv, and Web of Science for studies published between 2014 and 2025, with inclusion criteria requiring the application of XAI in inspection tasks using public or domain-specific datasets. From an initial pool of studies, 75 were included and categorized in
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Objectives: The study aim was to explore the knowledge, perceptions, and attitudes of Iraqi physicians regarding generic and locally manufactured medicines. Methods: A total of 124 physicians were involved in this cross -sectional study. The convenience sample was collected from five public hospitals in Baghdad. A self-administered questionnaire was distributed and collected in-person. Fisher's Exact Test was used to measure the association between physician years of experience, gender and categorical (perception and knowledge) variables. Results: Most respondent answers regarding the knowledge of generic medicines were incorrect. Only up to one-third of the participants knew that generic medicines are therapeutically eq
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<p class="0abstract">Image denoising is a technique for removing unwanted signals called the noise, which coupling with the original signal when transmitting them; to remove the noise from the original signal, many denoising methods are used. In this paper, the Multiwavelet Transform (MWT) is used to denoise the corrupted image by Choosing the HH coefficient for processing based on two different filters Tri-State Median filter and Switching Median filter. With each filter, various rules are used, such as Normal Shrink, Sure Shrink, Visu Shrink, and Bivariate Shrink. The proposed algorithm is applied Salt& pepper noise with different levels for grayscale test images. The quality of the denoised image is evaluated by usi
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This quasi-experimental study investigated generative AI (GenAI) tools—Copilot for chemistry and GitHub Copilot for mathematics—on academic achievement and sustainable professional development among 160 undergraduates (40 experimental/control per department) at the University of Baghdad’s Ibn Al-Haitham College of Education for Pure Sciences (2024–2025). Non-random assignment controlled for covariates. Pre/post validated tests (α ≥ .85; 15 MCQ + 5 essay items) measured outcomes. ANOVA revealed significant gains for experimental groups (p < .001, η2 = .41, Cohen’s d = 0.72 [95% CI: 0.45–0.98]). Chemistry excelled in affective domains; mathematics in cognitive/skills. Findings affirm GenAI’s domain-specific effica
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